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license: apache-2.0
tags:
- agi-forecast
- pac-bayes
- governance
- agentic-ai
- formal-verification
- ai-governance
- alignment
- bekenstein
- bayesian
- lean4
size_categories:
- n<1K
task_categories:
- other
language:
- en
pretty_name: AGI Forecast — Safety Forecasting Gauges Source
---
# agi-forecast — FG-01..FG-12 AI Safety Forecasting Gauges
[](https://www.apache.org/licenses/LICENSE-2.0)
[](https://doi.org/10.5281/zenodo.20434276)
Source mirror of [github.com/szl-holdings/agi-forecast](https://github.com/szl-holdings/agi-forecast). Forecasting models and scenario libraries for AI governance trajectories, grounded in PAC-Bayes stability bounds and Bekenstein information limits.
| Signal | Value |
|--------|-------|
| Forecast gauges | FG-01 through FG-12 |
| Scenarios | FG-S1 → FG-S4 |
| Grounding | PAC-Bayes + Bekenstein |
| Benchmark | Putnam 2026-05-27 |
| License | Apache-2.0 |
## Cross-links
- **Live viewer:** [SZLHOLDINGS/agi-forecast-viewer](https://huggingface.co/spaces/SZLHOLDINGS/agi-forecast-viewer)
- **Platform:** [SZLHOLDINGS/agi-forecast-platform](https://huggingface.co/spaces/SZLHOLDINGS/agi-forecast-platform)
- **Source:** [github.com/szl-holdings/agi-forecast](https://github.com/szl-holdings/agi-forecast)
## Citation (BibTeX)
```bibtex
@misc{lutar2026ouroboros,
title = {Ouroboros: Formal Verification of Agentic AI Governance — v18.0},
author = {Lutar, Stephen P.},
year = {2026},
doi = {10.5281/zenodo.20434276},
url = {https://doi.org/10.5281/zenodo.20434276}
}
```
## Contact
**Stephen P. Lutar** · stephen@szlholdings.com
[](https://orcid.org/0009-0001-0110-4173)
[github.com/szl-holdings](https://github.com/szl-holdings) · [huggingface.co/SZLHOLDINGS](https://huggingface.co/SZLHOLDINGS)
---
*Doctrine v6 strict — no marketing superlatives — every claim verifiable.*
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